No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Reactivated Wuwanchai landslide area monitoring and analysis
Abstract
Terrain that has previously experienced a landslide is subject to the additional threat of reactivated landslides. The reactivated Wuwanchai landslide is located in Chiayi County in southern Taiwan at Expressway No. 18. The reactivated landslide has exhibited slow movement with continuing creek headwater erosion. The landslide comprises eight sliding blocks that are categorized as main slipping blocks, slow-moving blocks, and activated blocks in accordance with their deformation characteristics. The reactivated landslide’s deformation characteristics and failure mechanisms were monitored using field investigations, airborne LiDAR surveys, and unmanned aerial vehicle (UAV) photogrammetry; the results were compared with traditional inclinometer monitoring of the displacement and groundwater level measurements. The concave terrain tends to collect surface water, and the level of the groundwater table tends to fluctuate due to seasonal precipitation. Geologic structures and headward creek erosion increased the sliding of the deposited colluvium. An interaction mechanism for the sliding blocks is proposed on the basis of the deformation characteristics, activity of the sliding blocks, topography changes, sliding masses, and UAV images. Separation of the landslide area in accordance with the deformation characteristics of the composed sliding blocks best explained the reactivation mechanism of the large-scale landslide.
... Drone images have been widely used for engineering applications (González-Jorge et al. 2017). These images are commonly employed to create digital terrain models (DTMs) or digital surface models (DSMs) for monitoring and analyzing the topographic characteristics of landslides (Rossi et al. 2018;Chen et al. 2022;Hussain et al. 2022). ...
This study employed a comprehensive methodology, which combines the use of multispectral images and field inclinometer data. The unique approach involves using multispectral images to monitor the topographic and hydrological changes caused by a large-scale landslide at Caoling in Taiwan. The field inclinometer data, collected at regular intervals, were then integrated into a geographic information system. This system was used to estimate the potential sliding volume of the landslide, which was then compared with changes in the digital terrain model data for Caoling. The multispectral images of Caoling were examined to determine the changes in its topographic and hydrological indices after the landslide. The convex slope at Caoling moved in the progressive backward mode with increased groundwater level and slope displacement under rainfall conditions. The potential sliding volume of the landslide was 6.4 × 10⁶ m³. The results of this study indicate that the changes in topographic and hydrological indices after a landslide enable the identification of the local surficial changes caused by the landslide. Changes in the rate of slope movement show a high correlation to the fluctuation of groundwater level. Reactivation of the large-scale landslide is attributable to hillslope, geologic and topographic characteristics, including toe creek incision, surficial erosion, and torrential rainfall brought by typhoons. Moreover, post landslide topographic monitoring through drone images, which provide high-resolution and real-time data, plays a crucial role in identifying a landslide’s reactivation mechanism. This, in turn, enables effective disaster mitigation strategies to be implemented.
... On the other hand, human activity-induced landslides often happen unexpectedly during the construction process, excavation, embankment compaction, urban development, and human engineering activities (Notti et al. 2015;Shang et al. 2017;Wu et al. 2018;Yao. 2018;Li et al. 2019;Chen et al. 2022;Zhao et al. 2022;Zhang et al. 2022). In particular, topographical change in humanaffected flow systems provides considerations for human-induced land cover variation and the impact of dam construction on the horizontal and vertical connections of watershed systems (Poepple et al. 2017). ...
On 9 August 2022, the Hoengseong landslide was induced by heavy precipitation at a solar power plant in Gangwon Province, South Korea. The slope failed at the embankment of the solar power plant and subsequently transited to a high-mobilized debris flow. The fluidized mass, solar panels, and drainage components rushed down to National Route No. 6 and destroyed all vegetation along the valley. The debris mass killed one person and destroyed two houses. The Hoengseong landslide was initiated and had a long-runout distance of about 330 m, a total drop of 60 m, and a landslide volume of 1.5 × 104. This study presents to analyze the kinematic characteristics of a landslide-generated debris flow event with the PFC3D numerical model and linear contact bonding method. In order to analyze the distinctions between different processes, a combination of field surveys, unmanned aerial vehicle (UAV) photogrammetry, and laboratory triaxial tests were utilized. These methods were employed to extract essential parameters, including the digital elevation model and shear strength, which are associated with the rheological properties of landslide-debris flow materials. In dynamic analysis, the velocity, displacement, and characteristics of landslide deposition were considered. The results indicate that the initial landslide stage started with overall acceleration, and the movement of soil mass lasted approximately 1000 s with double-peak velocity curves and nonsynchronous displacement. Based on the simulation results, it was determined that the landslide had an average velocity of 0.848 m/s and a local maximum velocity of 3.138 m/s. It was observed that around 400 to 600 s into the simulation, two houses were demolished and underwent significant deformation. The morphology of the deposit exhibited a satisfactory agreement with the findings of the on-site survey. By offering comprehensive insights into the Hoengseong landslide, this study serves as a valuable resource for enhancing our comprehension of landslide dynamics and mitigating the risks associated with the potential reactivation of the Hoengseong landslide.
S U M M A R Y In late June 2016, the Harmalière clayey landslide (located 30 km south of the city of Greno-ble, French Alps) was dramatically reactivated at the headscarp after a 35-yr-long period of continuous but limited activity. The total involved volume, which moved as sliding blocks of various sizes, was estimated to be about 2 × 10 6 m 3. Two seismometers were installed at the rear of the main headscarp in August 2016, on both sides of a developing fracture delineating a block with a volume of a few hundred cubic metres. For 4 months, they continuously recorded seismic ambient vibrations and microearthquakes until the block broke. Five seismic parameters were derived from the monitoring: the cumulative number of microearthquakes (CNe), the seismic energy (SE), the block resonance frequency (f B), the relative variation in Rayleigh wave velocity (dV/V) deduced from noise cross-correlations between the two sensors and the associated correlation coefficient (CC). All parameters showed a significant precursory signal before the rupture, but at very different times, which indicates the complexity of the rupture mechanism in this clay material.
In this study, an investigation on the formation mechanisms, deformation characteristics, and stability of the Outang landslide, composed by three independent blocks (O1, O2, and O3), is performed by integrating site surveys, multi-technique monitoring data, and numerical simulation. The results show that the formation mechanism for blocks O1 and O3 is slide-bulking, and is planar slide for block O2. These three blocks slide along the incompetent layers (ILs): IL1 is the slip surface of block O1 and O2, and IL3 is the slip surface of block O3. Furthermore, the west local fast movement zone might evolve into deep failure. The slope surface movement is step-like, characterized by the alternation of rapid displacement followed by imperceptible displacement over each hydrological year. The surface displacement velocities increased upslope. Based on the numerical simulation, both precipitation and reservoir water are believed as the major factors driving the slope behaviors, and the slope stability would be decreased gradually under the effect of the periodic variation of water level and seasonal precipitation infiltration. As a result of this study, some countermeasures of landslide and long-term monitoring are recommended.
In this study, we investigated a recent landslide that occurred in Zhouqu County, China. At 18:00 pm Beijing time on July 19, 2019, the Yahuokou landslide was reactivated. About 3.92 × 106 m3 of debris slumped from the slope, blocking the Minjiang River channel, causing the water level to rise, and disrupting road. Fortunately, there were no injuries. A field survey, remote sensing imaging, borehole core analysis, landslide monitoring, and rainfall data analysis were conducted to examine the geomorphologic and stratigraphic characteristics of the landslide, the reactivation causes, and the dynamic mechanism of the landslide. A model for the reactivation and evolution of the landslide is presented. The field survey of the sliding zone indicates that the landslide has a flow-slide deformation pattern. The landslide mechanism is summarized as follows. Initially, slow plastic flow sliding occurred in the upper sliding body. Then the platform in the middle gentle slope was preloaded by deposits from the upper part failure, resulting in a “cutting and filling” effect. The failure occurred in the form of creep–tension cracks–debris flow–slide. Finally, the block on the lower part slumped. Thus, the upper, middle, and lower parts of the landslide all transferred stress in the same manner, being activated step by step, and slowly slumped into the river.
Landslide is a global natural hazard that occurs frequently in the areas of incompetent weak rocks, undulating topography, steep slopes and incessant rainfall. In the night of 12 August 2017, a massive landslide took place at Kotrupi, Mandi district, Himachal Pradesh, India. The slide was so huge that it eroded more than 300-meter stretch of NH-154 killing over 50 people with more than 40 missing. Local residents report that this area has always been unstable where small landslides had occurred in the past. The landslide scar could be seen on the past satellite images from December 2001 to March 2017 on Google Earth. A huge landslide occurred at this location on 13 August 1977. After two decades on 13 August 1997, the landslide reactivated and some part of the slope failed, which can be seen on satellite images of the year 2001. The landslide reactivated again on 13 August 2007, but not much attention was given to it, as it was a small event and did not affect much. Again, after a decade, in the night of 12 August 2017 this landslide was reactivated. There is the possibility of reoccurrence of slope instability from upper reaches of the crown area of the main slide complex as well as the debris, which have been already accumulated on hill and valley side. Based on the geological, geotechnical and geophysical investigations the site stability can be done but its monitoring from satellite provides the information for its future preventive measures.
On 12 July 2018, the giant Jiangdingya ancient landslide reactivated and blocked the Bailongjiang River in Nanyu Town, Gansu Province, China. The ancient landslide was ca. 4.1~4.9 × 10⁷ m³, and the 2018 reactivated landslide was ca. 4.8~5.5 × 10⁶ m³, with the characteristics of a deep-seated retrogressive landslide. The terrain and geological structure of the landslide area are very complicated with alpine valleys and high gradient rivers, and the ancient landslide had maturely developed. The Pingding-Huama fault, which has been active since the late Quaternary, passed through the landslide region. Because of the active fault and tectonic uplift, the lithology is deeply fragmented. Based on the remote sensing interpretation and field investigation, development characteristics and reactivation mechanism of the Jiangdingya ancient landslide are described.
Landslides in the Podsljeme area of the City of Zagreb cause significant economic losses, which have been increasing over the last several decades due to the urbanisation of hilly areas and the influence of climate changes. An airborne LiDAR digital terrain model (DTM) with a spatial resolution of 30 × 30 cm was used to prepare a landslide inventory map of the pilot area (21 km²) with more than 700 identified landslides. The area of the smallest identified landslide is 43 m², while 90% of the landslides are between 100 and 2,000 m². The frequency–size distribution of all mapped landslides in the pilot area shows a very high level of landslide inventory completeness. Therefore, it is concluded that the LiDAR-based terrain model is a valuable tool for the preparation of detailed landslide inventories in heavily vegetated regions such as the hilly area of Medvednica Mt.
The re-activation of a large (40 Mm³) landslide on the valley slopes of a reservoir motivated a research initiative to estimate the risk of a fast-sliding mass moving into the reservoir. A previous simplified analysis had suggested that a joint consideration of strain rate effects on friction and thermal pressurization phenomena in the sliding surface could provide a rational approach to answer the question raised. The paper describes first the capability of strain rate effects on friction to reproduce long-term creeping records of two real cases. The joint and coupled phenomena of creeping motion and thermal pressurization in shearing bands was incorporated into a material point method computational technique for hydromechanical analysis of porous materials. A representative cross section of the Canelles landslide was then analysed, profiting from previous finite element investigations of the landslide. It was found that a rapid rate of landslide acceleration could be a possibility under extreme external actions. However, it was also found that a moderate strain rate effect on the basal residual friction angle could create conditions that avoid the triggering of a fast motion.
Episodically to continuously active slow‐moving landslides are driven by precipitation. Climate change, which is altering both the frequency and magnitude of precipitation worldwide, is therefore predicted to have a major impact on landslides. Here we examine the behavior of hundreds of slow‐moving landslides in northern California in response to large changes in annual precipitation that occurred between 2016 and 2018. We quantify the landslide displacement using repeat‐pass radar interferometry and pixel offset tracking techniques on a novel data set from the airborne NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar. We found that 312 landslides were moving due to extreme rainfall during 2017, compared to 119 during 2016, which was the final year of a historic multiyear drought. However, with a return to below to average rainfall in 2018, only 146 landslides remained in motion. The increased number of landslides during 2017 was primarily accommodated by landslides that were smaller than the landslides that remained active between 2016 and 2018. Furthermore, by examining a subset of 51 landslides, we found that 49 had increased velocities during 2017 when compared to 2016. Our results show that slow‐moving landslides are sensitive to large changes in annual precipitation, particularly the smaller and thinner landslides that likely experience larger basal pore‐water pressure changes. Based on climate model predictions for the next century in California, which include increases in average annual precipitation and increases in the frequency of dry‐to‐wet extremes, we hypothesize that there will be an overall increase in landslide activity.
Filling of Xiangjiaba Reservoir Lake in the Southwest China triggered and reactivated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at the right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out to identify the landslide with respect to its surroundings and to find out the slip surface. Boreholes were drilled to find out the subsurface lithology and the depth of failure of Dasha landslide. The in situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using the 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain is relatively steep. The total volume of landslides is about 580×104 m ³ with an average thickness of 20 m. Bedrock in the landslide area is composed of Suining Formation of the Jurassic age. The main rock type is silty mudstone with sandstone, and the bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown.
Remote sensing technologies have seen extraordinary improvements in both spatial resolution and accuracy recently. In particular, airborne laser scanning systems can now provide data for surface modeling with unprecedented resolution and accuracy, which can effectively support the detection of sub-meter surface features, vital for landslide mapping. Also, the easy repeatability of data acquisition offers the opportunity to monitor temporal surface changes, which are essential to identifying developing or active slides. Specific methods are needed to detect and map surface changes due to landslide activities. In this paper, we present a methodology that is based on fusing probabilistic change detection and landslide surface feature extraction utilizing multi-temporal Light Detection and Ranging (LiDAR) derived Digital Elevation Models (DEMs) to map surface changes demonstrating landslide activity. The proposed method was tested in an area with numerous slides ranging from 200 m2 to 27,000 m2 in area under low vegetation and tree cover, Zanesville, Ohio, USA. The surface changes observed are probabilistically evaluated to determine the likelihood of the changes being landslide activity related. Next, based on surface features, a Support Vector Machine (SVM) quantifies and maps the topographic signatures of landslides in the entire area. Finally, these two processes are fused to detect landslide prone changes. The results demonstrate that 53 out of 80 inventory mapped landslides were identified using this method. Additionally, some areas that were not mapped in the inventory map displayed changes that are likely to be developing landslides.
Active landslides have three major effects on landscapes: (1) land cover change, (2) topographical change, and (3) above ground biomass change. Data derived from multi-temporal Light Detection and Ranging technology (LiDAR) are used in combination with multi-temporal orthophotos to quantify these changes between 2006 and 2012, caused by an active deep-seated landslide near the village of Doren in Austria. Land-cover is classified by applying membership-based classification and contextual improvements based on the synergy of orthophotos and LiDAR-based elevation data. Topographical change is calculated by differencing of LiDAR derived digital terrain models. The above ground biomass is quantified by applying a local-maximum algorithm for tree top detection, in combination with allometric equations. The land cover classification accuracies were improved from 65% (using only LiDAR) and 76% (using only orthophotos) to 90% (using data synergy) for 2006. A similar increase from respectively 64% and 75% to 91% was established for 2012. The increased accuracies demonstrate the effectiveness of using data synergy of LiDAR and orthophotos using object-based image analysis to quantify landscape changes, caused by an active landslide. The method has great potential to be transferred to larger areas for use in landscape change analyses.
In this study, six different periods of digital terrain model (DTM) data obtained from various flight vehicles by using the techniques of aerial photogrammetry, airborne LiDAR (ALS), and unmanned aerial vehicles (UAV) were adopted to discuss the errors and applications of these techniques. Error estimation provides critical information for DTM data users. This study conducted error estimation from the perspective of general users for mountain/forest areas with poor traffic accessibility using limited information, including error reports obtained from the data generation process and comparison errors of terrain elevations. Our results suggested that the precision of the DTM data generated in this work using different aircrafts and generation techniques is suitable for landslide analysis. Especially in mountainous and densely vegetated areas, data generated by ALS can be used as a benchmark to solve the problem of insufficient control points. Based on DEM differencing of multiple periods, this study suggests that sediment delivery rate decreased each year and was affected by heavy rainfall during each period for the Meiyuan Shan landslide area. Multi-period aerial photogrammetry and ALS can be effectively applied after the landslide disaster for monitoring the terrain changes of the downstream river channel and their potential impacts.
Acoustic emission (AE) has become an established approach to monitor the stability of soil slopes. However, the challenge has been to develop strategies to interpret and quantify deformation behaviour from the measured AE. This paper presents the first comparison of continuous AE (measured using an active waveguide) and continuous subsurface deformation measurements. The active waveguide is installed in a borehole through a slope and comprises a metal waveguide rod or tube with a granular backfill surround. When the host slope deforms, the column of granular backfill also deforms, generating AE that can propagate along the waveguide. This paper presents results from a field trial at a reactivated soil slope in North Yorkshire, UK. The measurements confirm that AE rates generated are directly proportional to the velocity of slope movement (e.g. the AE rate versus velocity relationship determined for a series of slope movement events produced an R^2 value of 0.8) and demonstrate the performance of AE monitoring of active waveguides to provide continuous information on slope displacements and displacement rates with high temporal resolution.
The Three Gorges region of central western China is one of the most landslide-prone regions in the world. However, landslide detection based on field surveys and optical remote sensing and synthetic aperture radar (SAR) techniques remains difficult owing to the dense vegetation cover and mountain shadow. In the present study, an area of Zigui County in the Three Gorges region was selected to test the feasibility of detecting landslides by employing novel features extracted from a LiDAR-derived DTM. Additionally, two small sites—Site 1 and Site 2—were selected for training and were used to classify each other. In addition to the aspect, DTM, and slope images, the following feature sets were proposed to improve the accuracy of landslide detection: (1) the mean aspect, DTM, and slope textures based on four texture directions; (2) aspect, DTM, and slope textures based on aspect; and (3) the moving average and standard deviation (stdev) filter of aspect, DTM, and slope. By combining a feature selection method and the RF algorithm, the classification accuracy was evaluated and landslide boundaries were determined. The results can be summarized as follows. (1) The feature selection method demonstrated that the proposed features provided information useful for effective landslide identification. (2) Feature selection achieved an improvement of about 0.44% in the overall classification accuracy, with the feature set reduced by 74%, from 39 to 10; this can speed up the training of the RF model. (3) When fifty randomly selected 20% of landslide pixels (PLS) and 20% of non-landslide pixels (PNLS) (i.e., 20% of PLS and PNLS) were utilized in addition to the selected feature subsets for training, the test sets (i.e., the remaining 80% of PLS and PNLS) yielded an average overall classification accuracy of 78.24%. The cross training and classification for Site 1 and Site 2 provided overall classification accuracies of 62.65% and 64.50%, respectively. This shows that the random sampling design (which suffered some of the effects of spatial auto-correlation) and the proposed method in this present study contribute jointly to the classification accuracy. (4) Using the Canny operator to delineate landslide boundaries based on the classification results of PLS and PNLS, we obtained results consistent with the referenced landslide inventory maps. Thus, the proposed procedure, which combines LiDAR data, a feature selection method, and the RF algorithm, can identify forested landslides effectively in the Three Gorges region.
Slope failures world-wide cause many thousands of deaths each year and damage built environment infrastructure, costing billions of pounds to repair, resulting in thousands of people being made homeless and the breakdown of basic services such as water supply and transport. There is a clear need for affordable instrumentation that can provide an early warning of slope instability to enable the evacuation of vulnerable people and timely repair and maintenance of critical infrastructure. An approach, Assessment of Landslides using Acoustic Real-time Monitoring Systems (ALARMS) is described in the paper, and results of a field trial of sensors on an active landslide at Hollin Hill, North Yorkshire, UK, are described. Continuous and real-time monitoring of acoustic emission generated by the deforming slope has been compared to traditional inclinometer slope displacement measurements. Analysis of the results has established that there is a direct relationship between acoustic emission rate and displacement rate trends triggered by rainfall events. The technique has provided insight into reactivated slope movement kinematics.
Large-scale landslides often cause severe damage to lives and properties; therefore, their identification is essential in order to adopt proper mitigation measures. The objective of this study was to set up a methodological approach to help identify large-scale landslides using Lidar data, aerial photos and field investigation. The selected study areas were the Namasha and Liuoguey Areas in Kaohsiung City, Taiwan, both of which were severely hit by the Typhoon Morakot in 2009. The identification of large-scale landslides was performed based on Lidar high-resolution topographic information. The linear structures were mapped according to the shading map, with aspect in different azimuth to show good details of the structures. The scarps of the landslides were also identified. Validation of the results was done using both aerial photos and field investigations. In addition, stability analyses were performed on designated cases to further validate the results of Lidar identification.
In the framework of the WISELAND project, funded by MIUR, we tested the integration between LiDAR and hyperspectral methodologies in the Valoria landslide (Modena province, Italy), a high risk area with vulnerable elements, subjected to periodic and abrupt reactivations. Multitemporal LiDAR Digital Terrain Models (DTMs) allowed the calculation of a differential surface, highlighting absolute height variations, recognizing the main landslide components and identifying depletion and accumulation zones. Hyperspectral data helped in the landslide terrain roughness characterization, performing the Principal Component Analysis (PCA) and correlating the results with Flatness and Organization geomorphometric parameters derived from LiDAR DTM.
This paper presents a short history of the appraisal of laser scanner technologies in geosciences used for imaging relief
by high-resolution digital elevation models (HRDEMs) or 3D models. A general overview of light detection and ranging (LIDAR)
techniques applied to landslides is given, followed by a review of different applications of LIDAR for landslide, rockfall
and debris-flow. These applications are classified as: (1) Detection and characterization of mass movements; (2) Hazard assessment
and susceptibility mapping; (3) Modelling; (4) Monitoring. This review emphasizes how LIDAR-derived HRDEMs can be used to
investigate any type of landslides. It is clear that such HRDEMs are not yet a common tool for landslides investigations,
but this technique has opened new domains of applications that still have to be developed.
KeywordsLandslide–LIDAR–Laser scanner–High-resolution DEM–Topography analysis–Structural analysis
For understanding the distribution of slope angles, OHM and roughness of the rainfall-induced landslides in Alishan Area of Central Taiwan, a survey was carried out with airborne Lidar and aerial digital camera to obtain DEM and DSM of 1 m grid and color orthophotos of 50 cm grid. DEM, DSM and orthophotos are georeferenced and co-registered. The 106 landslide polygons derived from photo-interpretation are used for extracting slopes, OHM and roughness. Results show that the average slope angle of landslides is 41 degrees with a standard deviation of 14 degrees; average OHM is 4.4 m with a standard deviation of 6.3 m; average roughness is 2.05 m with a standard deviation of 2.56 m. It is also observed that scale effects are obvious for roughness but not for slope and OHM when the grid is larger than 40 m, which is the average dimension of landslides. These morphometric parameters can be further applied in the automation of landslide inventory.
Several examples in western Europe have shown that, at least for deep-seated rotational slides, reactivation of formerly slipped masses is a more frequent phenomenon than the occurrence of new landslides, therefore representing a higher hazard. We selected a study area comprised of 13 landslides located in the Flemish Ardennes (West Belgium) and predicted the hazard related to scarp retreat. The scarp reactivations were identified from the comparison of DTMs produced for 1952 and 1996. Robust results were obtained with the Gamma operator of a fuzzy set approach and a combination of geomorphic, topographic and land use data. We built first a prediction model from the relations linking the 1952?1996 retreat events to the conditioning parameters of 1952. The prediction rate of the resulting susceptibility map is estimated by a cross-validation procedure. We then applied the statistics of this model to the data of 1996 in order to produce a susceptibility map responding to the present-day conditions. Finally, we estimated the conditional probabilities of occurrence of future reactivations for the period 1996?2036.
This paper presents details of the recently reactivated landslide in Wushan Town, Chongqing, China. The landslide was reactivated on July 17, 2019, by slope cutting, and thereafter, entered a state of imminent sliding. The landslide involved 4 million m3 of rock and soil masses, thereby threatening National Road G348 and the safety of 588 residents in 136 households in Xiping Village and over 1000 residents in the Jinke Community. Field investigations, drilling, and in situ monitoring were performed to determine the landslide deformation characteristics and reactivation mechanism. The results show that the regional abundant rainfall, formation lithology, and tectonic effects were responsible for the formation of the ancient Baiyangwan landslide. Moreover, the building load on the rear and middle parts increased the sliding force. Open excavation at the toe decreased the anti-sliding force and directly promoted landslide reactivation. In particular, the groundwater table rise caused by gully filling in recent years also played a key role in the reactivation of the ancient landslide.
At approximately 2:00 p.m. (Beijing time) on August 6, 2019, the previously controlled Leidashi landslide was reactivated near group 7 of Zhangjiagou village, Jianyang County, Sichuan Province, China. The 2019 Leidashi landslide damaged two main roads and 44 antisliding piles and posed a threat to another main road. This landslide was a reactivation of the 2010 Leidashi landslide and had an accumulation zone of 2.2 × 106 m3. To explore the deformation characteristics and failure mechanism, detailed field investigations, unmanned aerial vehicle photogrammetry, airborne LiDAR surveys, borehole drilling and inclinometer installation were carried out, and the collected data were analyzed. The results show that the 2019 Leidashi landslide could be divided into main slipping zone and activated zone according to movement state, and the main slipping zone could also be divided into main scarp area, main deposit area, climbing area, uplift area, and local landslide area according to the local movement and geomorphic features. The rapidly increasing landslide thrust caused by short-term but continuous heavy rain caused the failure of the antisliding piles and ultimately reactivated the 2010 landslide.
The presence of large paleo-landslides can hinder the construction of railway lines if they cause an
alteration of the natural balance of the slope, significantly increasing the cost of the project. During
the construction works in a section of the Madrid-Asturias high-speed railway line (Spain), a large
scale hillside instability affected 460 m of the section. The ground movement began ten months
after the start of the excavations and remained active throughout the observation period (2008
2010). Data provided by fieldwork, boreholes and instrumental monitoring has allowed the
investigation of the geological units involved, together with the geometry and the kinematics of the
mass movement. This landslide involves a Paleozoic basement with an estimated volume of
4,400,000 m3. It shows low displacement rates (<45 mm/year) and was accommodated on a single
surface of rupture, that reaches more than 60 m in depth. The kinematics is favoured by structural
and lithological conditions, there being a strong rheological contrast in the lower part of the
mobilized ground. This movement is linked to a large paleo-landslide that was partially reactivated
when excavations undermined the lower slopes of the hillside. Technical solutions for the
stabilization have already caused an additional cost of 17% over the initial budget.
A precise, accurate and complete landslide inventory is indispensable for the establishment of reliable landslide susceptibility and hazard maps. In the preparation of landslide inventories, dense vegetation cover is the major obstacle that confounds the topographic signature of landslides. Today, the growing usage of light detection and ranging (LiDAR) technology in the field of geoscience illuminates the mystery of the landscapes cloaked in dense vegetation by providing a new visual acuity to researchers. Turkey, similar to many mid-latitude mountainous countries suffering from landslides, is still continuing landslide inventory mapping with conventional methods such as aerial photo interpretations (API), although 68% of landslide events occurred under dense forest cover in the north of the country. Despite the country-wide medium-scaled landslide catalogs, the number and the abundance of landslides covered by forests remain largely unknown regardless of the increasing availability of high-resolution remote-sensing data. From these motivating insights and drawbacks, the study's focus is to evaluate the capability of mapping landslides by visually analyzing airborne LiDAR DTM derivatives and compare the results with the 1:25,000 scaled API-based inventory to understand the potential contribution of LiDAR technology in Europe's deadliest country (Turkey) in terms of landslides. The landslide mapping results for a test area located in the densely forested Ulus Basin, Western Black Sea region, reveal that the extent and the number of the mapped landslides (n = 902) from the airborne LiDAR data are much higher than those of the available API-based landslide inventory, which includes 67 landslides. Comparative analysis on topographic signatures of landslides is also underpinned on a distinct discrepancy of slope failure diagnostic indicators captured by the two available DEMs derived from LiDAR and 1:25,000 scaled topographic maps, emphasizing the success rate of LiDAR-derived DEM in recognition and mapping landslides with higher precision and accuracy. Together with all analysis results, the landslide recognizability degree assessment based on the forest cover percentage and slope height differences of landslides highlights that the LiDAR data enable landslides to be defined up to 100 m2, while this value is 20 times lower than that of estimated values from API-based landslides. In addition to underlining the contribution of LiDAR technology to the recognition of landslides hidden under dense vegetation, these findings stress the importance of LiDAR data on complete and accurate landslide inventories for production of reliable susceptibility and hazard maps and further a better understanding of the landslide processes and reducing related losses.
An ancient landslide, situated in Deqin County, Yunnan Province, China, was used to investigate the reactivation by water infiltration. This study considers the infiltration process and landslide stability using finite-element method (FEM)-based models. The results show that the reactivation of old landslide deposit was triggered by the long-term leakage of diversion ditch before October 2012, and the reactivation was triggered again by the intense rainfall on 7–9 October 2012. The old cracks, which formed in the earlier reactivation of landslide, played a key role for the rainfall infiltration. They offered a preferential path for much more rainfall to infiltrate fast into deep soil, and caused wetting front to move down faster in landslide. The old slip zone with lower permeability was another important factor to cause the infiltrated water to accumulate and form a high pore water pressure above slip zone. Then the high pore water pressure decreased the shear strength of slip zone and triggered the reactivation of the old landslide deposit again.
Although landslides are a group of natural hazards, the factor causing their activation is often human activity. The construction of buildings and roads on slopes has an especially unfavourable impact on its stability. Additional load and disturbance of natural hydrological conditions are factors that may cause the reactivation of old landslides. This paper contains a case study of the activation of landslide processes, which was caused by human activity. In the area of the old and inactive landslide an educational complex was built. The complex consisted of four buildings located in one line across the slope. An additional, very unfavourable factor was the high level of groundwater, which was rising up to the ground surface temporarily. At the time of long-term rainfall activation of landslide processes in the substrate of the building occurred. These processes are characterized by slow changes, causing progressive destruction of buildings. The geological structure of the slope was determined by six core holes with a depth of about 20 m. On this basis, the geological layers, hydrological conditions and slide surface position were determined. Deformations of the slope and the building were monitored by using integrated survey techniques: precision leveling, electronic techeometry, traversing (angular-linear), static GNSS and laser scanning. The work includes the analysis of initial geological and hydrological conditions, the analy-sis of the causes and the course of deformation processes in the substructure, the results of the measurements and the analysis of the deformation of buildings caused by a landslide.
Landslides reactivate due to external environmental forcing or internal mass redistribution, but the process is rarely documented quantitatively. We capture the three‐dimensional, 1‐m resolution surface deformation field of a transiently reactivated landslide with image correlation of repeat airborne lidar. Undrained loading by two debris flows in the landslide's head, rather than external forcing, triggered reactivation. After that loading, the lower 2 km of the landslide advanced by up to 14 m in 2 yrs before completely stopping. The displacement field over those 2 yrs implies that the slip surface gained 1 kPa of shear strength, which was likely accomplished by a negative dilatancy‐pore pressure feedback as material deformed around basal roughness elements. Thus, landslide motion can be decoupled from external environmental forcing in cases, motivating the need to better understand internal perturbations to the stress field to predict hazards and sediment fluxes as landscapes evolve.
Landslides typically alter hillslope topography, but may also change the hydrologic connectivity and subsurface water-storage dynamics. In settings where mobile materials are not completely evacuated from steep slopes, influences of landslide disturbances on hillslope hydrology and susceptibility to subsequent failures remain poorly characterized. Since landslides often recur at the site of previous failures, we examine differences between a stable vegetated hillslope (VH) and a recent landslide (LS). These neighboring hillslopes exhibit similar topography and are situated on steep landslide-prone coastal bluffs of glacial deposits along the northeastern shore of Puget Sound, Washington. Our control hillslope, VH, is mantled by a heterogeneous colluvium, supporting a dense forest. In early 2013, our test hillslope, LS, also supported a forest before a landslide substantially altered the topography and disturbed the hillslope. In 2015, we observed a clay-rich landslide deposit at LS with sparse vegetation and limited root reinforcement, soil structures, and macropores. Our characterization of the sites also found matrix porosity and hydraulic conductivity are both lower at LS. Continuous monitoring during 2015–2016 revealed reduced effective precipitation at VH (due to canopy interception), an earlier seasonal transition to near-saturated conditions at LS, and longer persistence of positive pore pressures and slower drainage at LS (both seasonally and between major storm events). These differences, along with episodic, complex slope failures at LS support the hypothesis that, despite a reduced average slope, other disturbances introduced by landsliding may promote the hydrologic conditions leading to slope instability, thus contributing to the persistence of landslide hazards.
More than 5000 landslides or potential landslides have been induced in the Three Gorges Reservoir (TGR) region since the impoundment in 2003, which have caused great damage and remain a huge threat to the dam and people living in the reservoir area. Understanding the deformation characteristics and failure mechanism of the landslides can be helpful in stability evaluation and landslide prediction. The primary aim of this study is to research the characteristics of the landslide motion and its relationships with environmental triggers, taking the Quchi landslide, a large, slow-moving, reactivated landslide in the TGR region, as an example. The instability clearly showed visible signs of movements since 2002, and after that, the slope has been experiencing persistent deformation. By combining 4 years of meteorological, hydrological data with displacement measurements from open fractures, deep boreholes, and surface points, as well as in situ observations, this paper reports the geological and geotechnical investigations performed to define the movement. The deformation is believed to be governed by reservoir water levels, while the precipitation has a minor effect. Seasonally, the slope movement has a very distinctive pattern with large deformation starting abruptly right after reservoir drawdown in June and lasting into late summer (September). Then there is a rapid transition to constant deformation (almost no displacement) as the reservoir level rises. The slope displacements appear to gradually increase every year, which suggests very high possibility of the large and overall failure of the slide. Both monitoring results and geomorphological observations have highlighted that the two active slide masses Q1 and Q2 would probably collapse in different kinematic evolution modes, i.e., the multistage failure and whole sliding motion.
Landslides are natural phenomena for the dynamic balance of the earth's surface. Because of frequent occurrences of typhoons and earthquakes in Taiwan, mass movements are common threats to people's lives. In this paper, the interpretation of knowledge is quantified as recognition criteria. Multisource high-resolution data, for example, a SPOT satellite image, 20 m × 20 m Digital Terrain Model (DTM) reduced from Light Detection And Ranging (LiDAR) data, and aerial orthophotos were used to construct the feature space for landslide analysis. Landslides were recognized by an objectoriented method combining edge-based segmentation and a Supported Vector Machine (SVM) method. The classification results are evaluated in comparison with those by manual interpretation. Two cases from northern and central Taiwan are tested. Both cases show that the object-based SVM method is better than a pixel-based method in classification accuracy. The commission error of the proposed method is also smaller than that of the pixel-based method. Moreover, except for the spectral features, the slope and Object Height Model (OHM) characteristics are also important factors for improving landslide classification accuracy. Further study is required for assessing the mixed pixel effect when the resolution is as large as 20 m and for characterizing the effects of sampling rates or scaling caused by changes in resolution.
It has long been recognized that field hydrological and geomechanical properties/conditions are the key elements controlling the stability of a slope under the influence of rainfall. Warning systems based on rainfall or ground displacement measurements are popular methods currently being used to minimize the hazards of landslides. When field hydrological monitoring is used, it usually involves a limited number of sensors for either positive or negative pore-water pressure measurements. The available numerical schemes that couple pore-water pressure with a geomechanical analysis are the most suitable for shallow slope failures. Due to the variable and transient nature of the hydrological conditions in earth slopes, field measurements that reflect the pore-water pressure profile on a real-time basis would be highly desirable. Thus, the authors have developed a piezometer system that is based on optical fiber Bragg grating (FBG) pressure sensors. With this system, an array of nine sensors was installed in a single, 60-m-deep borehole to monitor the pore-water pressure profile in a highway slope in Southern Taiwan. This paper describes the details of the FBG sensor array installation in the field and the data obtained throughout three typhoons from 2008 to 2010. The results demonstrate that the field readings can be readily incorporated into the existing mechanics-based analytical framework and can predict the potential of an upcoming slope failure.
In this paper, a study of slope failures along the Alishan Highway (locally, known as “Tai-18”) is carried out. An innovative empirical model is developed based on 15-year records of typhoon rainfall-induced slope failures. This model is intended for assessing the likelihood of slope failure along Tai-18 in the future. The rainfall data considered in the proposed model include the maximum hourly rainfall and the effective cumulative rainfall. The effective cumulative rainfall is defined at the point when the curve of cumulative rainfall goes from steep to flat. Then, a simple criterion is established for assessing the potential of slope failure and issuing warning and/or closure for Tai-18 during a future extreme rainfall. Slope failures during Typhoon Saola in 2012 and those in Japan demonstrate that the new empirical model is effective and applicable to other regions with similar rainfall conditions.
The primary aim of this research was to study the relationship between landslide motion and its causes, with reference to large, slow moving, reactivated translational rock slides. Surface displacements of the 22 × 106 m3 Utiku landslide, in central North Island, New Zealand were measured using continuous GPS (cGPS), for three years. The nature of the movement of such slides has often been difficult to determine because of poor temporal and spatial monitoring resolutions. After removal of tectonic plate motion, the temporal pattern of the landslide's surface motion could be understood to arise from irregular episodes of faster (up-to-21 mm/day) and slower (up to 26 mm/yr) post-failure landslide displacement, and seasonal cyclic displacements of about 20 mm/yr–10 mm per half year in alternating directions. Intervals of faster motion gave rise to displacements of between 10 and 120 mm per event. Faster displacement was associated mostly with basal sliding (mechanism 1), involving deformation within a thin clay seam as recorded by borehole inclinometer surveys. Slower surface displacement involved permanent internal deformation of the larger landslide mass, consisting of plastic deformation within the landslide body and/or slip along existing internal planes of weakness, and slip on the slide base (mechanism 2); it accounted for up to 26 mm/yr of displacement at a mean angle of about 49° from the horizontal, indicating that the slide mass was thinning as it moved down slope. Seasonal cyclic displacements were synchronous with changes in pore pressure, suggesting that it is a shrink/swell process (mechanism 3) associated with wetting and recharge of groundwater during the wetter winter months, leading to a downslope movement, and soil shrinkage leading to upslope rebounds during the dryer summer months. The brief periods of faster displacement were triggered by seasonal peaks in pore pressure, linked to long periods (12 to 20 weeks) of increased precipitation and lowered evapotranspiration. Faster displacement, however, was not arrested by lowering pore pressure or by any other monitored factor. Similarly, periods of slower displacement did not correlate with pore pressure changes, or with any other monitored factor. This study has shown that the annual movement pattern of a reactivated landslide is a combination of these processes that generate a complex overall movement record. The field measurements showed real variability arising from variations in rainfall and pore pressure, which were overprinted with measurement noise that may mask some other processes.
Rainfall-induced up-slope failure has been a major issue for the mountain road mitigation. To determine the mitigation priority of the roadside slopes, a model to evaluate the stability of the up-slopes is proposed in this paper. This model is developed using Bayesian classification theorem, historical rainfall and landslide data, and an artificial intelligence skill-Gaussian process. The parameters needed for this model include the up-slope features, catchment area, lithology, vegetation coverage, and rainfall data. Among these parameters, rainfall is considered to be the triggering factor of landslide in this study. In addition, each slope has also demonstrated a unique failure probability relationship with the 72-h accumulated rainfalls. Such a relationship is adopted to define a threshold rainfall factor which is used as an index to estimate the likelihood of landslide occurrence under a rainfall event. Using the threshold rainfall factor of each slope, a priority list is proposed for the mitigation of roadside up-slopes along the Alishan mountain road in Taiwan.
This paper describes the reactivation of an ancient landslide during the construction of a fill buttress. Even though precautions were taken during construction of the buttress, such as excavating it in 30-m-long (100-ft-long) segments, the ancient landslide nevertheless was reactivated. The reactivated landslide moved laterally about 5-8 cm (2-3 in.), which resulted in significant damage, such as cracking to building foundations, walls, and ceilings, as well as distortion of door frames and windows. An interesting observation was that the ancient landslide, once activated, did not stop immediately after the buttress had been backfilled. The lateral movement continued for about 10 months, at a decreasing rate of movement. This movement was probably due to the slow closure of the ground cracks as well as the deformation of the landslide into the buttress. This case history illustrates the disadvantage of using a buttress to stabilize an ancient landslide, especially when the excavation is below the rupture surface.
Bell, R., Petschko, H., Röhrs, M. and Dix, A. Assessment of landslide age, landslide persistence and human impact using airborne laser scanning digital terrain models. Geografiska Annaler: Series A, Physical Geography, 94, 135–156. doi:10.1111/j.1468-0459.2012.00454.x
Landslides occur worldwide and contribute significantly to sediment budgets as well as to landform evolution. Furthermore, they pose hazards and risks to people and their goods. To assess the role of landslides, information on their age or persistence (i.e. the length of time the morphological characteristics of a landslide remain recognizable in the terrain) is essential. In this study, the potential of airborne laser scanning digital terrain models (ALS DTMs) is analysed for estimating landslide age, landslide persistence and human impact. Therefore, landslides in two study areas, Swabian Alb in Germany and Lower Austria in Austria, are mapped from hillshades of ALS DTMs and combined with historical information on landslide occurrence. It is tested whether the modification of the geomorphological features of landslides can be used to assess landslide age. In the Swabian Alb older landslides might show fresher features than younger ones because of different degrees of human impact, natural erosion and different histories of landslide reactivation. Estimated persistence times range between 27 and 320 years but are minimum values only. In Lower Austria four landslides show estimated minimum persistence times between 4 and 28 years. In Lower Austria 27 landslides disappeared in less than 7 years after occurrence mainly because of planation by farmers. The results show no clear trend in landslide persistence, neither regarding landslide magnitude, nor regarding land use. However, it is evident that human impact plays a major role in landslide persistence.
Landslides show a power-law distribution for frequency-area or -volume analysis. In Taiwan, landslides often block roads and expressways after torrential rains. Because available estimation methodology is limited, statistical analysis of expressway blockage is lacking. The purpose of this study is to identify the landslide characteristics and blockage length for a case study of a landslide along the Alishan expressway in Taiwan. The statistical analysis of the landslide frequency-blockage length distribution shows a power-law distribution. The probability of landslide blockage expressway length can be estimated in advance for further risk analysis.
The number of human-induced landslides is increasing worldwide, but information on the impact of human intervention on slope stability is often lacking. Therefore, this study analyses the Hekkebrugstraat landslide, the best-recorded landslide in the Flemish Ardennes (Belgium). Information obtained from local inhabitants, aerial photographs and newspaper articles enabled a 50-year reconstruction of both the landslide history and the land-use changes at or close to the landslide site. The reconstruction suggests that anthropogenic preliminary factors such as: (i) the absence of well-maintained drainage ditches in the affected area; (ii) the elevation of the surface of the road, i.e. a sunken lane, in the affected area; (iii) increased surface runoff from the drainage area; (iv) the creation of ponds; and (v) the removal of the lateral support at the landslide foot have played an important role in the reactivation of the Hekkebrugstraat landslide. After the reactivation of February 1995, landslide movement was observed for more than 5 years and caused damage to houses, and other infrastructure. However, also natural factors, such as the presence of an impermeable clay layer at limited depth, springs and relatively steep slopes (i.e. 0.14 m m−1), and above normal antecedent rainfall have contributed to the reactivations. Comparison of our reconstruction of the reactivation with precise Digital Terrain Models (DTMs) of 1952, 1973 and 1996, produced by digital stereophotogrammetry, indicated that the reported movements correspond well with the uplifted and collapsed zones found on the DTMs. Hence, this analysis provides valuable information for land-use planners in areas with old, apparently stable, landslides.
The first impoundment of the Three Gorges Dam reservoir in China started from a water surface elevation of 95m on June 1,
2003 and reached 135m on June 15, 2003. Shortly after the water level reached 135m, many slopes began to deform and some
landslides occurred. The Qianjiangping landslide is the largest one; it occurred on the early morning of July 14, 2003 and
caused great loss of lives and property. Field investigation revealed that, although failure occurred after the reservoir
reached 135m, the stability of the slope was already reduced by preexisting sheared bedding planes. To study the mechanism
of the rapid motion of this reactivated landslide, two soil samples were taken from a yellow clay layer and a black silt layer
in the sliding zone, respectively, and a series of ring shear tests were conducted on the samples. One series of ring shear
tests simulates the creep deformation behavior, while the other series simulates different shear rates. Conclusions drawn
from analysis of the ring shear tests indicate that the mechanism of the rapid motion of the reactivated landslide was caused
by the rate effect of the black silt layer during the motion phase after the creep failure. The yellow clay layer did not
play any important role in the rapid motion in the 2003 event.
This paper is aimed at creating an empirical model for assessing failure potential of highway slopes, with a special attention to the failure characteristics of the highway slopes in the Alishan, Taiwan area prior to, and post, the 1999 Chi-Chi, Taiwan earthquake. The basis of the study is a large database of 955 slope records from four highways in the Alishan area. Artificial neural network (ANN) is utilized to “learn” from this database. The developed ANN model is then used to study the effect of the Chi-Chi earthquake on the slope failure characteristics in the Alishan area. Significant changes in the degrees of influence of several factors (variables) are found and possible reasons for such changes are discussed. The novelty of this paper lies in the fact that the developed ANN models are used as a tool to investigate the slope failure characteristics before and after the Chi-Chi earthquake.
In order to clarify the relationship between rain and/or meltwater (MR), pore-water pressure and landslide displacement, continuous monitorings were conducted at a reactivated landslide comprised mainly of weathered mudstone of Tertiary in age. An exponential relationship was found between the total amount of MR at each event and the amount of pore-water pressure increment integrated by time (impulse of pore-water pressure). In addition, as the total MR increased, the difference between the minimum and maximum values of pore-water pressure for each event (fluctuation range of pore-water pressure) also increased, but the intensity of MR had little effect on the fluctuation range of pore-water pressure. The correlation coefficient for the fluctuation range of pore-water pressure and cumulative landslide displacement, and that for the impulse of pore-water pressure and cumulative displacement were similar, but were only 0.57 to 0.66. On the other hand, the correlation coefficient for the total MR and cumulative landslide displacement was large (0.65–0.69). Cumulative landslide displacement was very highly correlated with effective MR (which shows the estimated water content in the ground) for a half-life period of 4 days, and correlation coefficients were 0.89–0.92. Thus, the displacement characteristics of this reactivated landslide which has a long history of landsliding can be explained using the hydrological factor of water content rather than the hydraulic characteristics of pore-water pressure.
Expressway high precision Lidar survey and interactive 3D GIS management system setting
- Hafdmed
Application of Airborn LiDAR surveying on slopes of No. 18 expressway 34K-96K. Highway Administration Fifth District Maintenance Engineering Department, Results report of Chung Hsing Surveying Company Limited
- Hafdmed
Assessment of landslide volume for Alishan highway based on database of rainfall-induced slope failure
- Y Y Chi
- Y F Lee
- YY Chi
Application of LIDAR-derived DEM for detection of mass movements on a landslide. Int Arch Photogramm Remote Sens Spat Inf Sci XL-5/W3
- M Barbarella
- M Fiani
- A Lugli
18 expressway 28.9 km-31.5 km landslide investigation, remediation planning and safety evaluation
- Hafdmed
Expressway Woo-Wan-Chai section monitoring and management system maintains and update service
- Hafdmed